ENGN 1610 Image Understanding

Pedro Felzenszwalb
Email: pff (at) brown.edu

Lectures: MWF 2:00-2:50 PM Barus & Holley 157

Office hours: Monday 3-4 PM

Course description
Image processing is a technology experiencing explosive growth; it is central to medical image analysis and transmission, industrial inspection, image enhancement, indexing into pictorial and video databases, e.g., WWW, and to robotic vision, face recognition, and image compression. This senior-level undergraduate course covers theoretical underpinnings of this field and includes a series of practical MATLAB image processing projects. ENGN 1570 is recommended but not required.

Image formation
Low-level image processing
3D reconstruction
Motion estimation
Image segmentation
Object recognition

Computer Vision: Algorithms and Applications. Szeliski. Springer.
A draft PDF is available here.


Topic 1: Image Formation
Topic 2: Image Filtering and Edge detection
Topic 3: Multiview geometry and stereo matching
Topic 4: Dynamic Programming
Topic 5: Image Segmentation
Topic 6: Graph algorithms
Topic 7: Template matching
Topic 8: Distance transform and Hausdorff matching
Topic 9: Convolutional Neural Networks
Topic 10: Geometric Methods for Recognition
Topic 11: Motion and Optical flow

Readings Assignments

1) Szeliski chapter 2
2) Edge detection Handout and Additional examples
3) Szeliski chapter 11
4) Sections 3 and 5 of this survey
5) Mean shift and feature space analysis
6) Slides on distance transforms and Hausdorff matching


Using images in MATLAB: example.m

Assignment 1 and test images
Due: Friday September 28

Assignment 2 and test images
Due: Friday October 12

Assignment 3 and files
Due: Tuesday October 26

Assignment 4 and files
Due: Monday November 26